The clinical usefulness of measurement of visceral fat area using multi frequency bioimpedance: The association with cardiac and renal function in general population with relatively normal

This study was performed to determine the clinical usefulness of measurement of visceral fat area (VFA) using bioimpedance analysis in relation with left ventricular hypertrophy (LVH), diastolic dysfunction parameters, and decreased estimated glomerular filtration rate (eGFR).

International Journal of Medical Sciences

2017; 14(13): 1375-1381 doi: 10.7150/ijms.21393

Research Paper

The Clinical Usefulness of Measurement of Visceral Fat Area Using Multi-Frequency Bioimpedance: The

Association with Cardiac and Renal Function In General Population with Relatively Normal Renal Function

Hye Eun Yoon1, 2,Sang Su Choi1, 2, Yaeni Kim1, 2, and Seok Joon Shin1, 2 

1 Division of Nephrology, Department of Internal Medicine, Incheon St Mary’s Hospital, Incheon, Korea;

2 Division of Nephrology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea

 Corresponding author: Seok Joon Shin, MD, PhD, Division of Nephrology, Department of Internal medicine, Incheon St Mary’s Hospital, College of Medicine, The Catholic University of Korea, 56 Dongsu-ro, Bupyung-gu, Incheon, Republic of Korea, 21431 Tel: 82-32-280-5091, Fax: 82-32-280-5987 E-mail: imkidney@catholic.ac.kr

© Ivyspring International Publisher This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/) See http://ivyspring.com/terms for full terms and conditions

Received: 2017.06.09; Accepted: 2017.10.11; Published: 2017.11.02

Abstract

Background: This study was performed to determine the clinical usefulness of measurement of

visceral fat area (VFA) using bioimpedance analysis in relation with left ventricular hypertrophy (LVH),

diastolic dysfunction parameters, and decreased estimated glomerular filtration rate (eGFR)

Methods: A cross-sectional analysis was performed on 1028 patients with eGFR≥60 ml/min/1.73m2,

aged 40 – 64 years, and who underwent routine health check-ups Subjects were divided into tertiles

based on their VFA Associations of VFA with echocardiographic parameters and eGFR were evaluated

Results: Across the VFA teriltes, there was a significant trend for increasing left ventricular mass index

(LVMi), left atrial diameter (LAD), and ratio of early mitral inflow velocity to peak mitral annulus velocity

(E/E’ ratio) and that for decreasing ratio of early to late mitral inflow peak velocities (E/A ratio) and

eGFR In multivariate linear regression analysis, log-transformed VFA was significantly associated with

increased LVMi, LAD, and E/E’ ratio, and with decreased E/A ratio and eGFR After adjustment for body

mass index, log-transformed VFA remained as a significant determinant for E/A ratio

Conclusion: VFA may be associated with LV structure and diastolic function, and decreased eGFR in

middle-aged adults with normal or mildly impaired renal function

Key words: visceral fat; bioimpedance analysis; glomerular filtration rate; echocardiography; left ventricular

hypertrophy; diastolic dysfunction

Introduction

Obesity is associated with increased left

ventricular (LV) mass and impaired LV systolic and

diastolic function, and elevated risk of cardiovascular

disease (CVD) [1, 2] Obesity is also related with an

increased risk of chronic kidney disease (CKD) in

middle-aged and older adults [3, 4] Body mass index

(BMI) is a well-known index for obesity, but it cannot

discriminate between fat mass and lean body mass

and does not account for fat distribution [5] In normal

aging, body fat undergoes redistribution, a

disproportionate increase in visceral adiposity as

opposed to subcutaenous adiposity [6] Therefore, the single use of BMI as an index of obestiy may have limits to reflect the visceral adiposity One of the tools

to assess visceral adiposity is to measure visceral fat area (VFA) The gold standard method to measure VFA is computed tomography [7], however its use is limited as a screening tool for the general population Multi-frequency bioimpedance analysis (BIA) is

a tool for measuring body composition, including lean mass, fat mass, and hydration status [8] Advances in BIA techology have allowed VFA to be measured [9]

Ivyspring

International Publisher

There are little data on the clinical usefulness of VFA

measured by BIA in the general population, especially

in middle-aged adults with relatively healthy renal

function This study was performed to evaluate the

clinical significance of VFA measured by BIA in terms

of LV structure and function and renal function, in

middle-aged adults with relatively normal renal

function

Methods

Study population

We retrospectively recruited subjects who is

from 40 to 64 years old and underwent health

Health Promotion Center as part of a voluntary

medical check-up between January 2012 and

December 2014 Subjects who had undergone

biochemical studies, echocardiography and BIA were

enrolled (n = 1032) We excluded individuals with an

estimated glomerular filtration rate (eGFR) less than

using the abbreviated Modification of Diet in Renal

Disease Study equation [10] A total of 1028 subjects

were included in the final analysis This study was

approved by the institutional review board of Incheon

St Mary's Hospital, Incheon, Korea

Data collection

Medical history and social-behavioral

information were collected through questionnaires

Physical examinations were performed by measuring

height, weight, waist circumference (WC), and blood

pressure (BP) according to standardized methods

During the measurements, the subjects were barefoot

and wore light clothes Before the measurement of BP,

the subjects rested in a sitting position for 10 minutes

BMI was calculated by dividing weight by height

squared (kg/m2) Blood samples were collected after

an overnight fast Fasting plasma glucose (FPG), and

levels of fasting insulin, serum creatinine, total

cholesterol (TC), triglyceride (TG), high-density

lipoprotein-cholesterol (HDL-C), low-density

lipoprotein-cholesterol (LDL-C), and C-reactive

protein were measured Subjects were considered to

have hypertension if they had a systolic BP of 140

mmHg or greater and/or a diastolic BP of 90 mm Hg

or greater or if they were being treated for

hypertension Subjects were considered to have

diabetes if he or she had a FPG of ≥126 mg/dL that

was first detected in this examination, used an

anti-diabetes medication, or was previously

diagnosed with diabetes by a doctor Dyslipidaemia

was defined as a TG concentration of 150 mg/dL or

greater or an LDL-C concentration of 100 mg/dL or

greater and/or taking cholesterol-lowering

medication A history of CVD was defined as a previous stroke, angina, or myocardial infarction VFA was measured using multi-frequency BIA (In-Body 720; Biospace, Seoul, Korea) The degree of insulin resistance assessed by homeostasis model assessment of insulin resistance (HOMA-IR) was calculated as follows: HOMA-IR = fasting insulin (mU/mL) x FPG (mmol/L)/22.5 [11]

Echocardiography

A two-dimensional-guided M-mode echocardio-graphy was performed by a cardiologist who was blind to the patient’s clinical and laboratory data M-mode measurements included left ventricular end-diastolic diameter (LVDd), left ventricular end-systolic diameter (LVDs), left ventricular posterior wall thickness (PWT), and interventricular septal thickness (IVST) Left ventricular mass (LVM) was calculated by means of the Devereux formula and indexed to height2.7 to determine the left ventricular

criteria used to define left ventricular hypertrophy

values of 50 g/m2.7 for men and 47 g/ m2.7 for women Left ventricular ejection fraction (LVEF), and left atrial diameter (LAD) were determined from apical 2- and 4-chamber views by the Simpson’s biplane formula, based on the recommendations of the American Society of Echocardiography [13] To estimate diastolic function, mitral inflow velocities, and myocardial tissue velocities were recorded using pulsed wave Doppler and the tissue Doppler, respectively From the mitral valve inflow velocity curve using pulsed wave Doppler, peak early diastolic flow velocity (MV-E), peak late diastolic flow velocity (MV-A), a ratio of E wave, and A wave (E/A ratio) were measured [14] From tissue Doppler imaging, septal mitral annular early peak velocity (E’) was measured A ratio of peak early transmitral flow velocity (E) to peak early diastolic mitral annular velocity (E/E’ ratio), that is an estimate of left ventricular filling pressure, was also calculated [15] High LAD was defined LAD > 35 mm, High E/E’ ratio as E/E’ > 7.9 and low E/A ratio as E/A ratio <

10.5, according to the median values

Statistical analysis

Subjects were divided into tertiles according to VFA values: tertile 1 (≤102.6 cm2), tertile 2 (102.6–127.1

cm2), and tertile 3 (>127.1 cm2) Differences in the baseline characteristics between the tertiles were evaluated Continuous data were expressed as the mean ± SD or as the median with interquartile range (25th to 75th percentile) in case of skewed distribution, and were compared using one-way ANOVA or the

Kruskal–Wallis test, as appropriate Categorical data

were expressed as numbers (percentage) and

compared using the chi-squared test Pearson

correlation analysis was performed to examine the

association between log-transformed VFA (logVFA)

and various parameters Multivariate linear

regression analysis was used to assess the association

of logVFA with eGFR, and echocardiographic

parameters after adjusting for confounding factors P

values of <0.05 were considered statistically

significant

Results

Baseline characteristics according to the VFA

tertiles

The clinical characteristics of 1028 subjects

stratified by VFA tertiles are shown in Table 1

Subjects in the highest VFA tertile were more likely to

be older, men, smokers, and those with BMI

dyslipidaemia The highest VFA tertile group had

higher systolic and diastolic BP, WC, and BMI levels,

than the middle and lowest VFA teritle groups

Subjects in the highest VFA tertile had higher FPG,

HOMA-IR, TC, TG, LDL-C, and C-reactive protein

levels, and lower HDL-C and eGFR levels compared

with those in the middle and lowest VFA tertile

groups

Association between logVFA values and clinical and echocardiographic parameters

LogVFA was positively correlated with age and levels of systolic and diastolic BP, WC, BMI, FPG, HOMA-IR, TC, TG, LDL-C, and C-reactive protein, LVMi, LAD, and E/E’ ratio, while it was negatively correlated with HDL-C level, eGFR, and E/A ratio After age- and sex-adjustment, logVFA was positively correlated with systolic and diastolic BP, WC, BMI, FPG, HOMA-IR, TC, TG, LDL-C, C-reactive protein, LVMi, LAD, and E/E’ ratio, and negatively correlated with HDL-C and E/A ratio (Table 2)

Association between VFA tertiles and LVH, high LAD, high E/E’ ratio, low E/A ratio and eGFR <90 ml/min/1.73m2

Table 3 shows the comparisons of LVMi, LAD, E/E’ and E/A ratios, and eGFR, and the prevalence of LVH, high LAD, high E/E’ ratio, low E/A ratio and eGFR <90 ml/min/1.73m2 The levels of LVMi, LAD, and E/E’ ratio increased as the VFA levels increased The prevalence of LVH, high LAD, and high E/E’ ratio also increased as the VFA levels increased The levels of E/A ratio and eGFR decreased, and the prevalence of low E/A ratio significantly increased as the VFA levels increased However, the prevalence of eGFR <90 ml/min/1.73m2 was not different between VFA tertiles

Table 1 Clinical characteristics of subjects

VFA Tertile 1

≤ 102.6 cm 2 Tertile 2 102.6 – 127.1 cm 2 Tertile 3 > 127.1 cm 2

P

TG (mg/dL) 103.0 (75.0 – 144.8) 140.5 (101.8 – 190.3) 165.0 (118.0 – 227.3) <0.001

C-reactive protein (mg/L) 0.38 (0.21 – 0.83) 0.63 (0.34 – 1.17) 0.93 (0.54 – 1.82) <0.001

eGFR (ml/min/1.73m 2 ) 107.9 (93.8 – 115.4) 103.4 (92.1 – 112.2) 105.5 (91.7 – 115.5) 0.008

CVD, cardiovascular disease; BP, blood pressure; WC, waist circumference; BMI, body mass index; FPG, fasting plasma glucose; HOMA-IR, homeostasis model assessment

of insulin resistance; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; eGFR, estimated glomerular filtration rate

Table 2 Correlations between log-transformed VFA and clinical and echocardiographic parameters

BP, blood pressure; WC, waist circumference; BMI, body mass index; FPG, fasting plasma glucose; HOMA-IR, homeostasis model assessment of insulin resistance; TC, total cholesterol; TG, triglyceride; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; eGFR, estimated glomerular filtration rate; LVMi, left ventricular mass index; LVEF, left ventricular ejection fraction; LAD, left atrial diameter; E/A ratio, ratio of early to late mitral inflow peak velocities; E/E’ ratio, ratio of early mitral inflow velocity to peak mitral annulus velocity a Tested by log-transformed value

Table 3 Mean or median levels of LVMi, LAD, E/E’ and E/A ratio and eGFR and prevalence of LVH, high LAD, high E/E’, low E/A ratio and

eGFR <90 ml/min/1.73m2 according to VFA tertiles

eGFR (ml/min/1.73m 2 ) 107.9 (93.8 – 115.4) 103.4 (92.1 – 112.2) 105.5 (91.7 – 115.5) 0.008

LVMi, left ventricular mass index; LVEF, left ventricular ejection fraction; LAD, left atrial diameter; E/E’ ratio, ratio of early mitral inflow velocity to peak mitral annulus velocity; E/A ratio, ratio of early to late mitral inflow peak velocities; eGFR, estimated glomerular filtration rate

Table 4 Association between logVFA levels and LVMi, LAD, E/E’ ratio, E/A ratio and eGFR

ß (95% CI) P ß (95% CI) P ß (95% CI) P ß (95% CI) P ß (95% CI) P

logVFA 13.88

(8.11, 19.65) <0.001 12.37 (10.19, 14.55) <0.001 1.94 (0.91, 2.96) <0.001 -0.34 (-0.48, -0.21) <0.001 -10.65 (-20.43, -0.86) 0.033

logVFA 5.04

(-1.58, 11.67) 0.136 7.12 (4.66, 9.58) <0.001 0.84 (-0.35, 2.03) 0.165 -0.27 (-0.42, -0.12) 0.001 -9.73 (-21.13, 1.66) 0.094

logVFA -7.19

(-14.89, 0.51) 0.067 1.33 (-1.51, 4.16) 0.359 0.08 (-1.33, 1.48) 0.913 -0.22 (-0.40, -0.03) 0.02 -2.64 (-16.10, 10.82) 0.700 Model 1: Adjusted for age, sex, diabetes, systolic BP, diastolic BP, smoking, alcohol drinking, dyslipidaemia, and history of CVD Model 2: Adjusted for model 1 + BMI as a categorical variable (BMI <25 kg/m 2 vs BMI≥25 kg/m 2 ) Model 3: Adjusted for model 1 + BMI as a continuous variable

Association between logVFA and LVMi, LAD,

E/E’ ratio, E/A ratio and eGFR

Multivariate linear regression analysis was

performed to examine the continuous association

between logVFA with LVMi, LAD, E/E’ ratio, E/A

ratio, and eGFR (Table 4) LogVFA was linearly

associated with LVMi (ß = 13.88, P < 0.001), LAD (ß =

12.37, P < 0.001), E/E’ratio (ß = 1.94, P < 0.001), E/A ratio (ß = -0.34, P < 0.001), and eGFR (ß = -10.65, P =

0.033) in model 1 In model 2, which included BMI as

a categorical variable, the association remained

significant for LAD (ß = 7.12, P < 0.001) and E/A ratio (ß = -0.27, P = 0.001) In model 3, which included BMI

as a continuous variable, the association remained

significant only for E/A ratio (ß = -0.22, P = 0.02) In

model 3, BMI was a significant determinant for LVMi

(ß = 1.33, P < 0.001), LAD (ß = 0.70, P < 0.001), E/E’

ratio (ß = 0.12, P < 0.001) and E/A ratio (ß = -0.008, P =

0.05)

Discussion

The results of our study showed that VFA

measured by BIA was associated with LV structure

and diastolic function and renal function in

middle-aged adults VFA was associated with

increased LV mass, LAD, and E/E’ ratio and

decreased E/A ratio and eGFR In multivariate linear

regression analysis including BMI, the association

remained significant for E/A ratio These findings

suggest that measurement of VFA using BIA may be

useful to identify milddle-aged adults with increased

risks of cardiac or renal diseases, especially for

detecting changes in mitral valve flow velocities

Visceral obesity is known to increase in normal

aging [6], and directly affects inflammation and

insulin resistance [16] The visceral fat component is

metabolically active and regulates adipokines and

cytokines which are associated with increased

cardiometabolic risk, including leptin, adiponectin,

plasminogen activator-1 and vascular endothelial

growth factor [17-20] In our study, subjects in the

highest VFA tertile group were more likely to be older

and smoker and to have diabetes, hypertension, or

dyslipidaemia Their systolic and diastolic BP, WC,

BMI, FPG, lipid levels, and C-reactive protein were

higher and they had higher insulin resistance The

correlation analyses also showed positive associations

of logVFA with levels of systolic and diastolic BP,

WC, BMI, FPG, HOMA-IR, lipids, and C-reactive

protein after age- and sex-adjustment These findings

support that VFA is related with hypertension,

metabolic abnormalities and inflammation, all of

which increase the risk of CVD

Previous reports showed the effect of obesity on

LV structure and function based on BMI [21, 22]

Visceral adiposity measured by computed

tomography was associated with increased LAD and

LVMi and decreased LV systolic and diastolic

function [23-25], while subcutaneous fat did not [23]

The results of our study extend these findings to a

younger population (mean age 52 years) The VFA

measured by BIA was associated with increased

LVMi, LAD, and E/E’ ratio and decreased E/A ratio

Especially, the association of VFA with E/A ratio

remained significant even after adjusting for BMI

Animal studies showed that accumulation of lipids in

the myocardium is related with cardiac dysfunction in

obese rats [26], and that therapeutic interventions to

reduce visceral adiposity improved cardiac

hypertrophy in Western diet-fed mice [27] In human,

TG accumulation in the myocardium increased with aging and was independently associated with LV diastolic dysfunction [28] Therefore, myocardial accumulation of lipids may be a potential mechanism

by which increased visceral adiposity mediates structural and functional change of LV In our study, the VFA level was not a better determinant for LVMi, LAD, and E/E’ ratio than BMI However, VFA showed a closer relationship with E/A ratio than BMI did These findings suggest that measurement of VFA using BIA may be useful to detect early changes in mitral valve flow velocities

There are previous reports on the association between obesity and renal function Obesity measurements including BMI, WC and fat mass measured by BIA were associated with increased risk

of rapid eGFR loss and the strongest OR for rapid eGFR loss was observed when baseline eGFR was < 60

showing that obesity, defined by the BMI, was not per

se a risk of CKD (eGFR < 60 ml/min/1.73m2) [29, 30], but a metabolically abnormal obesity is a risk of CKD [30] Since BMI cannot discriminate between fat mass, lean body mass and visceral adiposity [5], it cannot represent the metabolical abnormality or inflammation A recent cross-sectional study demonstrated that VFA measured by BIA was

[31] The authors reported that the prevalence of CKD ranged from 6.9% to 25.2% according to VFA tertile groups Our study also evaluated the association between VFA level and eGFR However, the difference was that the study population of this study

those who have relatively healthy renal function In this study, the eGFR levels decreased as the VFA tertile increased, and the logVFA showed a negative relationship with eGFR after adjustment for age, sex, diabetes, systolic and diastolic BP, smoking, alcohol drinking, dyslipidaemia, and history of CVD However, when BMI was included in the multivariate analysis, neither logVFA nor BMI was a significant determinant for eGFR We speculate that the cross-sectional design of our study had limits to show the effect of VFA on renal function in middle-aged adults with relatively healthy renal function

Recently it was published that visceral adiposity measured by computed tomography was a risk factor for renal function decline in elderly subjects without baseline CKD [32] Multiple mechanisms underlie the association between obesity and CKD Visceral adiposity is involved in inflammation, oxidative stress, and insulin resistance [33], and leads to the activation of the sympathetic nervous system and renin-angiotensin systems, lipid deposition and

increased sodium absorption in the kidneys resulting

in hypertension and decline in renal function [34] It

was also demonstrated that hypertension mediates

the association between obesity and CKD

development [35] In our study, VFA was related with

hypertension, dyslipidaemia, insulin resistance, and

inflammation Therefore the association between VFA

and eGFR may be mediated by metabolic

abnormality, hypertension and inflammation These

findings suggest that VFA can be a modifiable risk

factor for the decline of eGFR in subjects with

relatively healthy renal function

Strengths of our study include a specified

population, middle-aged adults with eGFR ≥60

LV structure and function and renal function

However our study has several limitations First, it

was a retrospective, cross-sectional analysis from a

single center Second, the causal relationship between

VFA and cardiac and renal function could not be

determined Third, the effect of specific medications

could not be assessed as the medical and

social-behavioral information were collected through

questionnaires Fourth, the advantage of VFA over

BMI for predicting LV structural and functional

changes and renal function was not clearly shown

from our study

In conclusion, high VFA levels were associated

with high levels of LVMi, LAD, and E/E’ ratio and

low levels of E/A ratio and eGFR These findings

suggest that VFA may be associated with the

development of LVH, diastolic dysfunction, and

decline of eGFR in middle-aged adults with normal or

mildly impaired renal function Measurement of VFA

using BIA could be useful to identify subjects at

increased risk of cardiac disease or CKD Further

research is needed to determine the role of VFA on

cardiac and renal diseases

Acknowledgement

This research was supported by the Basic Science

Research Program through the National Research

Foundation of Korea (NRF) funded by the Ministry of

(2014R1A1A3A04050919)

Competing Interests

The authors have declared that no competing

interest exists

References

1 Jee SH, Sull JW, Park J, et al Body-mass index and mortality in Korean men

and women N Engl J Med 2006; 355: 779-87

2 Lavie CJ, Ventura HO, Messerli FH Left ventricular hypertrophy Its

relationship to obesity and hypertension Postgrad Med 1992; 91: 131-2, 5-8,

41-3

3 Kramer H, Luke A, Bidani A, Cao G, Cooper R, McGee D Obesity and prevalent and incident CKD: the Hypertension Detection and Follow-Up Program Am J Kidney Dis 2005; 46: 587-94

4 de Boer IH, Katz R, Fried LF, et al Obesity and change in estimated GFR among older adults Am J Kidney Dis 2009; 54: 1043-51

5 Heymsfield SB, Cefalu WT Does body mass index adequately convey a patient's mortality risk? Jama 2013; 309: 87-8

6 Hughes VA, Frontera WR, Roubenoff R, Evans WJ, Singh MA Longitudinal changes in body composition in older men and women: role of body weight change and physical activity Am J Clin Nutr 2002; 76: 473-81

7 Micklesfield LK, Evans J, Norris SA, et al Dual-energy X-ray absorptiometry and anthropometric estimates of visceral fat in Black and White South African Women Obesity (Silver Spring) 2010; 18: 619-24

8 Jackson AS, Pollock ML, Graves JE, Mahar MT Reliability and validity of bioelectrical impedance in determining body composition J Appl Physiol (1985) 1988; 64: 529-34

9 Ogawa H, Fujitani K, Tsujinaka T, et al InBody 720 as a new method of evaluating visceral obesity Hepatogastroenterology 2011; 58: 42-4

10 Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation Modification of Diet in Renal Disease Study Group Ann Intern Med 1999; 130: 461-70

11 Bonora E, Kiechl S, Willeit J, et al Prevalence of insulin resistance in metabolic disorders: the Bruneck Study Diabetes 1998; 47: 1643-9

12 de Simone G, Devereux RB, Roman MJ, Alderman MH, Laragh JH Relation of obesity and gender to left ventricular hypertrophy in normotensive and hypertensive adults Hypertension 1994; 23: 600-6

13 Schiller NB, Shah PM, Crawford M, et al Recommendations for quantitation

of the left ventricle by two-dimensional echocardiography American Society

of Echocardiography Committee on Standards, Subcommittee on Quantitation

of Two-Dimensional Echocardiograms J Am Soc Echocardiogr 1989; 2: 358-67

14 Rakowski H, Appleton C, Chan KL, et al Canadian consensus recommendations for the measurement and reporting of diastolic dysfunction

by echocardiography: from the Investigators of Consensus on Diastolic Dysfunction by Echocardiography J Am Soc Echocardiogr 1996; 9: 736-60

15 Nagueh SF, Middleton KJ, Kopelen HA, Zoghbi WA, Quinones MA Doppler tissue imaging: a noninvasive technique for evaluation of left ventricular relaxation and estimation of filling pressures J Am Coll Cardiol 1997; 30: 1527-33

16 Schrager MA, Metter EJ, Simonsick E, et al Sarcopenic obesity and inflammation in the InCHIANTI study J Appl Physiol (1985) 2007; 102: 919-25

17 Hayashi T, Boyko EJ, Leonetti DL, et al Visceral adiposity is an independent predictor of incident hypertension in Japanese Americans Ann Intern Med 2004; 140: 992-1000

18 Mertens I, Van Gaal LF Visceral fat as a determinant of fibrinolysis and hemostasis Semin Vasc Med 2005; 5: 48-55

19 Wajchenberg BL Subcutaneous and visceral adipose tissue: their relation to the metabolic syndrome Endocr Rev 2000; 21: 697-738

20 Miyazawa-Hoshimoto S, Takahashi K, Bujo H, Hashimoto N, Saito Y Elevated serum vascular endothelial growth factor is associated with visceral fat accumulation in human obese subjects Diabetologia 2003; 46: 1483-8

21 Wong CY, O'Moore-Sullivan T, Leano R, Byrne N, Beller E, Marwick TH Alterations of left ventricular myocardial characteristics associated with obesity Circulation 2004; 110: 3081-7

22 Park J, Kim SH, Cho GY, et al Obesity phenotype and cardiovascular changes

J Hypertens 2011; 29: 1765-72

23 Canepa M, Strait JB, Milaneschi Y, et al The relationship between visceral adiposity and left ventricular diastolic function: results from the Baltimore Longitudinal Study of Aging Nutr Metab Cardiovasc Dis 2013; 23: 1263-70

24 Park J, Kim NH, Kim SH, et al Visceral adiposity and skeletal muscle mass are independently and synergistically associated with left ventricular structure and function: the Korean Genome and Epidemiology Study Int J Cardiol 2014; 176: 951-5

25 Fox CS, Gona P, Hoffmann U, et al Pericardial fat, intrathoracic fat, and measures of left ventricular structure and function: the Framingham Heart Study Circulation 2009; 119: 1586-91

26 Zhou YT, Grayburn P, Karim A, et al Lipotoxic heart disease in obese rats: implications for human obesity Proc Natl Acad Sci U S A 2000; 97: 1784-9

27 Mells JE, Fu PP, Sharma S, et al Glp-1 analog, liraglutide, ameliorates hepatic steatosis and cardiac hypertrophy in C57BL/6J mice fed a Western diet Am J Physiol Gastrointest Liver Physiol 2012; 302: G225-35

28 van der Meer RW, Rijzewijk LJ, Diamant M, et al The ageing male heart: myocardial triglyceride content as independent predictor of diastolic function Eur Heart J 2008; 29: 1516-22

29 Foster MC, Hwang SJ, Larson MG, et al Overweight, obesity, and the development of stage 3 CKD: the Framingham Heart Study Am J Kidney Dis 2008; 52: 39-48

30 Hashimoto Y, Tanaka M, Okada H, et al Metabolically healthy obesity and risk of incident CKD Clin J Am Soc Nephrol 2015; 10: 578-83

31 Kang SH, Cho KH, Park JW, Yoon KW, Do JY Association of visceral fat area with chronic kidney disease and metabolic syndrome risk in the general population: analysis using multi-frequency bioimpedance Kidney Blood Press Res 2015; 40: 223-30

32 Madero M, Katz R, Murphy R, et al Comparison between Different Measures

of Body Fat with Kidney Function Decline and Incident CKD Clin J Am Soc

Nephrol 2017; 12: 893-903

33 Odegaard JI, Chawla A Pleiotropic actions of insulin resistance and

inflammation in metabolic homeostasis Science 2013; 339: 172-7

34 Aneja A, El-Atat F, McFarlane SI, Sowers JR Hypertension and obesity Recent

Prog Horm Res 2004; 59: 169-205

35 Griffin KA, Bidani AK Progression of renal disease: renoprotective specificity

of renin-angiotensin system blockade Clin J Am Soc Nephrol 2006; 1: 1054-65